This specification relates to monitoring the energy consumption of electrical loads.
Control systems are commonly used to manage and control electrical loads (e.g., lighting systems, HVAC equipment, etc.) in commercial and residential environments (e.g., an office building, a home residence). Such control systems can be used to conserve energy in the commercial or residential environments, which can reduce energy costs and promote energy efficiency. For example, a facility manager can utilize a control system to automatically turn off office lights after the occupants have left the building for the day or to adjust the set points of the facility's heating and cooling system to reduce demand on and energy consumption by the heating and cooling system during weekends when the building is not occupied (e.g., lower the heating set point during winter months and raise the cooling set point during summer months).
In addition to managing the operation of the electrical loads, it is also desirable to determine how much energy is being consumed by the various electrical loads. Energy monitoring systems are one tool that can be utilized to monitor energy consumption. Energy monitoring systems can cooperate with control systems to further enhance energy conservation by providing feedback to the control system or facility manager indicating the energy consumed by the various electrical loads. This feedback can be used to adjust the management of the electrical loads or to make informed decisions about energy use. For example, if the energy monitoring system indicates that a particular light assembly is consuming energy to light a space during nighttime hours when persons are not usually present, the light assembly may be dimmed to reduce its energy consumption. The dimmed level may be such that the space is still sufficiently lit so that people may walk through the space safely.
The monitoring of energy consumption can also be useful for partnering with energy providers (e.g., utilities and utility commissions) that are pursuing public and technology policies that will allow the providers to “smooth” energy consumption over peak usage periods. By efficiently managing energy usage, the energy providers can avoid the need to build new power stations and distribution infrastructure, resulting in significant cost savings and energy conservation. These cost savings can be passed on to the energy consumers that partner with the providers.
Current energy consumption monitoring systems balance trade-offs are cost, accuracy and granularity. For example, energy consumption can be inferred based on the known states of the loads (e.g., on, off and dimming level) and the data from the load manufacturer detailing the operational parameters of the load (e.g., power requirements). Employing this type of inferential monitoring can provide, at a relatively low cost, highly granular results as each device or circuit containing a device or devices can be monitored. However, because this technique relies on inferential calculations to determine the energy consumed by the load, as contrasted with measuring the energy consumed, some inaccuracies may result.
Another monitoring practice is to place a power meter on a circuit. A circuit may be of any size, and may have dozens, if not hundreds, of power consuming devices. This approach has a low-to-moderate cost (e.g., the cost is for the power meter, and is proportional to how many power meters are used, or the ratio of power meters to power consumption devices), and can also be very accurate (e.g., commercial-grade power meters often target 0.2% accuracy to comply with ANSI C 12.20 and IEC687 requirements. However, this approach has a very low granularity.
Yet another approach is to measure power directly for each power consumption device. An emerging practice is to place low-cost power meters within every device, or in some cases, on very small circuits (e.g., two to three power consuming devices). A power consuming device might be a light fixture for highly granular information. While this approach is highly granular and accurate, the cost is very high compared to the other approaches (e.g., each power meter may cost several dollars or more).
Another trade-off that may need to be considered is coverage of a power monitoring circuit. For example, a building electrical grid may be such that a power meter monitoring a circuit may pick up loads used by other tenants in a multi-tenant facility and/or loads not under control of the control system, e.g., such as power to cubicles (task lights, computers, and the like) or security systems, etc. This issue is more common when placing power meters on circuits, since there may not be sufficient granularity. Conversely, power meters may not pick up some of the loads under control. This is more common in the first and third approaches, but is less common for the second approach, because the second approach monitors entire circuits and hence will pick up all loads.